Machine Learning Engineer
$160K–$200K+ Offers For Graduates $160K–$200K+ Offers For Graduates 

3 weeks remote, 7 weeks onsite in Austin, TX
80–100 hours/week for 10 weeks
In-person
Short-term contract
full-time (90 hrs/week)

Machine Learning Engineer   $160K–$200K+ Offers For Graduates $160K–$200K+ Offers For Graduates 

Description

Most engineers claim they want to build systems that matter. This is your opportunity to deliver on that: continuous shipping, rigorous assessment, and production AI systems that directly influence how the U.S. government functions. No résumé posturing. No abstract exercises. Only deployable output each week, under real pressure.

Gauntlet for America is a fully funded, competitive 10-week fellowship built to develop AI-native engineering talent for United States government operations. It serves as a high-stakes proving ground for seasoned engineers ready to show they can construct and deploy production-quality AI systems in settings where security, reliability, and tangible impact are paramount.

Participants ship each week, work under rigorous evaluation, and train with other top-tier engineers. Upon successful completion, fellows transition into federal GS-12 engineering positions (~$150K + comprehensive federal benefits), contributing to systems that directly shape government operations.

The fellowship spans 10 weeks: 3 weeks conducted remotely, then 7 weeks onsite in Austin, Texas. Participants should anticipate an intensive workload (80–100 hours/week) structured to accelerate learning velocity, signal clarity, and career advancement.

Outcomes:

  • 10+ production-grade AI systems delivered throughout the fellowship
  • Direct transition into a federal engineering position (GS-12 equivalent, ~$160K–$200K+ based on experience + full benefits)
  • Contribute to high-stakes systems that define how the U.S. government builds and deploys technology
  • Access a network of AI-native engineers working at the cutting edge of public sector innovation

If you're prepared to be judged on your output — not your academic pedigree — apply today.

What you will be doing

  • Deliver production-ready AI applications weekly against strict timelines
  • Develop using modern AI-first methodologies (agents, tool integration, evaluations, retrieval, deployment)
  • Work and compete with elite engineering peers in a feedback-intensive setting
  • Engage with authentic, ambiguous problem domains similar to government and enterprise contexts
  • Convert real project briefs into scoped, dependable, shippable systems

What you will NOT be doing

  • Attending theoretical lectures or passive coursework — every hour is dedicated to building and deployment
  • Waiting extended periods to see your work in production — you'll release functioning systems each week
  • Depending on credentials, academic background, or interview skills to secure placement — only your production output determines success
  • Operating in a low-risk environment — the systems you create must meet genuine security and reliability standards

Key responsibilities

Deliver production-grade AI systems under authentic constraints that validate readiness for federal engineering positions.

Candidate requirements

  • U.S. citizenship required (no exceptions; background check required)
  • Demonstrated engineering ability (new grads and experienced engineers considered)
  • Willing to relocate to Austin, TX for 7 weeks (full-time, in person)
  • Willing to relocate to the Washington, DC area upon program completion (no remote roles)
  • Strong problem-solving ability, learning speed, and clear reasoning under pressure
  • High responsiveness to feedback and ability to operate in high-intensity environments

Meet a successful candidate

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Fabiano Lucchese
Fabiano  |  SVP of Software Engineering
Brazil

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Applying for a role? Here’s what to expect.

Crossover's skill assessment process combines innovative AI power with decades of human research, to take the guesswork, human bias, and pointless filters out of recruiting high-performing teams.

Chat-style
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STEP 1

Chat-style
screening interview.

Cognitive 
aptitude test.
STEP 2

Cognitive 
aptitude test.

Prove real-world 
job skills.
STEP 3

Prove real-world 
job skills.

Interview with the hiring manager.
STEP 4

Interview with the hiring manager.

Pass
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STEP 5

Pass
proctored test.

Accept job offer.
STEP 6

Accept job offer.

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What you will learn

Phase 1: Remote (Weeks 1–3) — AI-First Engineering Foundations

  • AI-first development workflows (coding agents, MCP, real-time collaboration)
  • Retrieval-Augmented Generation (RAG), embeddings, and vector databases
  • Rapid project sprints focused on shipping under constraints

Phase 2: Onsite in Austin (Weeks 4–10) — Production AI at Scale

  • Agent systems, evals, verification, and observability (LangChain/LangSmith/LangFuse/CrewAI)
  • Enterprise-grade delivery: QA, reliability, and high-standards execution
  • Fine-tuning + deployment patterns (LoRA/QLoRA + production integration)
  • Multi-agent modernization of real-world codebases
  • Multimodal AI builds (image/video/voice) and scalable infrastructure (AWS/Azure)

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Premium pay for premium talent

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